Article Per Year (5 Year)
p-Index From 2021 - 2026
0.23
P-Index
This Author published in this journals
All Journal Jurnal Informatika: Jurnal Pengembangan IT
Viktor Wahyu Nugroho
Universitas Dian Nuswantoro
Computer Science & IT

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
Sentiment Analysis of Shopee Application Reviews Using Multinomial Naïve Bayes and Bigram Feature Extraction Viktor Wahyu Nugroho
Jurnal Informatika: Jurnal Pengembangan IT Vol 11, No 2 (2026)
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/jpit.v11i2.10074

Abstract

– The rapid growth of e-commerce in Indonesia has made user reviews a critical source of feedback, yet discrepancies between star ratings and actual sentiment often mislead businesses. This study employs the Multinomial Naïve Bayes algorithm to analyze sentiment in 25,000 Shopee application reviews collected via web scraping. The research utilizes TF-IDF for feature extraction and Bigram analysis to capture contextual meaning, addressing the challenge of imbalanced data (82% positive, 18% negative). The objective is to accurately classify user sentiment into positive and negative categories to provide actionable insights beyond numerical ratings. The model achieved a classification accuracy of 91.96%, with a high Recall of 77% for the minority negative class, ensuring effective identification of user complaints. Bigram analysis revealed that "delivery speed" is the primary driver for both satisfaction and dissatisfaction. The study confirms that Naïve Bayes is a robust and scalable solution for large-scale sentiment analysis in the Indonesian e-commerce context, offering a reliable tool for business intelligence
Co-Authors